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Record W645603552

Scientists and Swindlers: Consulting on Coal and Oil in America, 1820–1890

2008· book· en· W645603552 on OpenAlexaboutno aff
Paul Lucier

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaWork (physics)Petroleum industryService (business)Political scienceNarrativeEngineeringEnvironmental ethicsManagementHistoryBusinessArchaeologyArtMarketingEconomics
DOInot available

Abstract

fetched live from OpenAlex

In this impressively researched and highly original work, Paul Lucier explains how science became an integral part of American technology and industry in the nineteenth century. Scientists and Swindlers introduces us to a new service of professionals: the consulting scientists. Lucier follows these entrepreneurial men of science on their wide-ranging commercial engagements from the shores of Nova Scotia to the coast of California and shows how their innovative work fueled the rapid growth of the American coal and oil industries and the rise of American geology and chemistry. Along the way, he explores the decisive battles over expertise and authority, the high-stakes court cases over patenting research, the intriguing and often humorous exploits of swindlers, and the profound ethical challenges of doing science for money. Starting with the small surveying businesses of the 1830s and reaching to the origins of applied science in the 1880s, Lucier recounts the complex and curious relations that evolved as geologists, chemists, capitalists, and politicians worked to establish scientific research as a legitimate, regularly compensated, and respected enterprise. This sweeping narrative enriches our understanding of how the rocks beneath our feet became invaluable resources for science, technology, and industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.008
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.190
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2008
Admission routes1
Has abstractyes

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